Table REF  shows that F-VLM is very competitive among the published results. Compared to the leading RegionCLIP [1]} which uses additional caption pretraining, F-VLM directly uses a frozen CLIP backbone. In fact, F-VLM significantly surpasses the CLIP-R50 pretrained version of RegionCLIP, which does not leverage pretraining on caption data. Compared to other approaches, F-VLM offers better performance without the use of detection-tailored pretraining, weakly supervised learning, or knowledge distillation.
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